Canadian Forest Service Publications

Bivariate pheromone-based monitoring of spruce budworm larvae (Lepidoptera: Tortricidae). Rhainds, M.; Therrien, P.; Morneau, L.; Leclair, G. 2018. Journal of Economic Entomology 111(1): 277-282.

Year: 2018

Issued by: Atlantic Forestry Centre

Catalog ID: 39131

Language: English

Availability: PDF (download)

Available from the Journal's Web site.
DOI: 10.1093/jee/tox331

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Mark record


A bivariate approach to pheromone-based monitoring is developed for the spruce budworm, Choristoneura fumiferana (Clem.) (Lepidoptera: Tortricidae). The approach uses captures of males at pheromone traps for generation t (♂t) as a transitive term between densities of overwintering larvae in consecutive generations (L2t, L2t+1), based on a large data set including >2,000 observations in the province of Quebec (QC) between the interval 1992 and 2010. Although estimates of L2t and ♂t are autocorrelated to some extent, multi-year assessments of larval densities combined with pheromone trapping are justified by the complementarity (statistical significance) of both L2t and ♂t in predicting L2t+1 for 15 of 18 pairs of 2-yr intervals. Bivariate pheromone-based thresholds (number of males corresponding to specific transitions in larval densities between L2t and L2t+1) are reported for each year. As expected, thresholds for stable populations (L2t = L2t+1) were lower than for populations with positive growth rate (L2t < L2t+1). The thresholds derived in this study have limited heuristic value; however, because they vary greatly from year to year.

Plain Language Summary

Pest management of forest insects relies on effective forecasting of future populations (when and where epidemic populations arise). We develop here a novel mathematic approach to predict local density of spruce budworm based on past counts of larval density combined with capture of males at pheromone traps. The approach is used to derive pheromone-based thresholds (number of males that correspond to specific transitions of larval densities between years) within a range of density that are relevant to the Early Intervention Strategy.